Do you have a passion for building data products? Do you dream of working with customers on their most forward-looking ML initiatives? Are you experienced in deploying models in production? Do you deeply understand principles of A/B experimentation?
If you answered "yes" to these questions, please consider joining the MLS&D Machine Learning Ops team. We are a start-up like group that engages data science partners in MSFT and work alongside them to build a new breed of intelligent solutions and systems. We are looking for an Applied Machine Learning Scientist with strong analytical and Python/Spark development skills to join our team.
The most successful candidates will have several years of real-world experience building production ML/AI systems and applying machine learning algorithms across a breadth of modern technology platforms. They are customer focused and practical, enjoy challenging projects and have strong analytical skills, technical aptitude, software engineering, applied research, communication skills and a collaborative work style.
5+ years of experience with end-to-end ML implementation, including data pre-processing, feature engineering, building and tuning of ML models during training and in production.
Strong proficiency in Python programming.
Degree in Computer Science, Systems Engineering, Statistics, or equivalent technical/engineering domain or equivalent applied experience.
5+ (post MS) or 7+ (post BS) years of solid understanding of common statistical and machine learning techniques, both classical machine learning and deep learning.
Strong proficiency in Python ML/NLP frameworks, and at least one major programming language such as C#.
Experience with application development practices and version control systems.
Experience with working on big data pipelines and cloud solutions.
Experience with working in Microsoft Azure ML or another cloud-based ML platform, and MLFlow/MLeap, or similar services is a plus.
Ability to work independently and in a team, take initiative and lead engagements as required, and communicate effectively with customers and your colleagues.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Developing and deploying solutions with Microsoft Partners for solving business problems using machine (deep) learning and Bayesian a/b testing.
End-to-end execution of the data science process, from understanding business requirements, data discovery and extraction, model development and evaluation, to production pipeline implementation.
Building production level ML/AI solutions, with good software engineering and ML/AI principles.
Creating a platform for managing experiments and measuring impact through scorecards.
Designing the architecture and platform moving forward to support experimentation at all levels of the stack (cloud infra, micro-services, visualization, etc.)